Risk and Predisposition in the Tendency Theory of Causation

Article excerpt

Abstract:

Just as society has advanced and developed, the complexity of etiologic causes of disease has also progressed, creating numerous causal relationships to be identified and explored in healthcare research. Likewise, the concept of causation has become more complicated and grown to include the science of behaviors and outcomes. Cause and effect are believed to be the basis of risk and prediction; however, this paper challenges the idea of risk as a predictor of health outcomes and highlights the necessity of including causal principles in risk and predisposition. A basic understanding of theories and research models identifying cause and effect will aid nurses in their efforts to provide evidence-based research and practice.

Key Words: Causality, Probability, Prediction, Risk factors for chronic disease

Just as the freedom of the will is an experiential category of our psychic life, causality may be considered as a mode of perception by which we reduce our sense impressions to order.

-Niels Bohr (1987)

Introduction

Athough nurses strive to decrease a patient's risk for an adverse outcome, such as a disease, most healthcare providers and the public at large perceive risk in terms of acute conditions that can be treated and eradicated like an infection. This perception of risk may stem from Koch's postulates: a) Causative organisms can be isolated and experimentally transmitted, and b) symptoms occur soon after the onset of infection in a higher proportion of infected individuals (Cochran, Ewald, & Cochran, 2000). In industrialized countries, however, risk has become associated with chronic diseases, which often include complex and insidious symptomatology. Just as society has advanced and developed, the complexity of diseases has also progressed. Although single, etiologic causes of disease are fairly well known and managed, the nature of multiple etiologic diseases and their causes has only recently become evident. The link between multiple etiologies and outcomes makes the idea of risk and the concept of cause and effect less clear. Accurate assessment of disease risk and causation requires more extensive understanding guided by theory.

Although nurses are familiar with risk in healthcare practice, many do not understand the research or theoretical processes of risk assessment. Understanding the basis of research and the principles of statistics applied in exploring health outcomes is a valuable tool to inform evidence-based, nursing practice. The development of a risk theory allows for accurate testing and prediction of disease risk. Without a realistic understanding of risk theory and the concept of cause and effect, nurses may make erroneous assumptions that affect the quality of practice and compromise interventions.

Bridging the Gap

A gap exists in the nursing literature regarding cause and effect. In the past, nursing research focused on behavior observation progressing to behavior manipulation. With the increased complexity of chronic disease, however, nursing research embraces the notion of bio-behavioral research, breaking an old Cartesian division of behavior and biology. The concept of cause and effect has grown to include the science of behaviors and outcomes. In order to affect health outcomes, nurses must accept the complexity of human behaviors and biological processes and be capable of identifying significant causal relationships for further study and manipulation. Although causation is believed to be the basis of risk prediction, this paper challenges the idea of risk as a predictor of health outcomes and highlights the necessity of including causal principles in evaluating risk and predisposition in healthcare research. A better understanding of theories guiding healthcare research to identify cause-and-effect relationships will improve care quality through evidence-based nursing practice.

Risk, Theory and Research

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In healthcare and nursing practice, the words "risk," "probability," "cause and effect," and "prediction" evoke the confidence of facts, but in reality they may only be based on unfounded theoretical assumptions. …